The AI infrastructure buildout across Asia Pacific is generating capital requirements that conventional bank lending cannot keep pace with. Private credit has become the financing of choice for the developers, operators, and investors building the backbone of the region's AI economy.
Published by
Donald Klip | Co-Founder, Global Mortgage Group | Head, GMG Capital Advisory
30 years of institutional finance. Former hedge fund founder. Senior roles at top global investment banks. GMG Capital Advisory arranges private credit and special situations finance of $10M–$100M for operating companies across Asia Pacific.
[email protected] | +65 9773 0273 | Singapore · Hong Kong | Asia-Pacific
Every AI model trained, every AI inference run, every AI application deployed requires compute infrastructure, and that infrastructure is data centres. The explosion in AI adoption across Asia Pacific is translating directly into unprecedented demand for data centre capacity. Singapore, Malaysia (Johor), Indonesia, Japan, South Korea, India, and Australia are all experiencing record levels of data centre investment. The capital requirements are enormous and growing. And the banking system is not keeping pace.
AI Infrastructure Finance is one of the most active and underserved sectors in Asia Pacific private credit. The capital is available, if you know where to find it.
Why Banks Are Pulling Back from This Sector
AI infrastructure is a new asset class for many bank credit committees. The hyperscaler-driven demand dynamic, where Microsoft, Google, Amazon, and Meta are committing billions to regional data centre capacity, is poorly understood at the credit committee level in most banks. Banks apply legacy data centre credit frameworks to a fundamentally different market, resulting in conservative underwriting that leaves significant capital gaps. Power infrastructure requirements add a further dimension: AI compute is extraordinarily power-intensive and securing power at scale requires capital investment that conventional bank credit frameworks struggle to accommodate.
Collateral and Security in This Sector
Hyperscaler offtake contracts: Agreements with Microsoft, Google, Amazon, and Meta for dedicated capacity. These contracts, typically 10–15 years, from investment-grade counterparties, represent the gold standard of data centre collateral.
GPU and compute infrastructure: High-performance GPU clusters represent significant capital assets. Contracted utilisation from enterprise or research customers provides cash flow support.
Power infrastructure: Dedicated power feeds, on-site generation, and renewable energy agreements. Long-term power security is a critical value driver for AI data centres.
Land and building: The underlying real estate, particularly in land-scarce markets like Singapore where data centre-zoned land commands substantial premiums.
GMG Capital Advisory in This Sector
GMG Capital Advisory is actively engaged in AI infrastructure financing across Asia Pacific. We understand the hyperscaler contract dynamics, the power procurement landscape, and the GPU supply chain considerations that determine credit quality in this fast-moving sector. Contact us to discuss your AI infrastructure financing requirement.
About GMG Capital Advisory
Donald Klip | Co-Founder, Global Mortgage Group | Head, GMG Capital Advisory
Donald Klip has 30 years of institutional finance experience spanning hedge fund management and senior roles at the world’s top global investment banks. GMG Capital Advisory specialises in arranging and structuring corporate debt financing of $10M–$100M for operating companies, asset owners, and project sponsors where conventional bank lending is unavailable, insufficient, or too slow. We operate across 23+ jurisdictions in Asia Pacific.
www.gmg.asia | [email protected] | +65 9773 0273 | Singapore · Hong Kong
The Debt Desk
Corporate private credit intelligence for Asia Pacific’s $10M–$100M middle market. Published by GMG Capital Advisory. Part of the Private Credit Asia content series.
www.gmg.asia | Read all 41 articles in the series
